• DocumentCode
    257517
  • Title

    Grey discrete parameters model and its application

  • Author

    Yingjian Qi ; Zhengpeng Wu ; Ying Li ; Jing Yu

  • Author_Institution
    Fac. of Sci. & Technol., Commun. Univ. of China, Beijing, China
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    399
  • Lastpage
    404
  • Abstract
    To solve the problem that the growth of prediction of discrete grey model is constant, the paper establishes a new grey discrete parameters prediction model by instructing quadratic time-varying parameters, which is called as quadratic time-varying discrete grey model(referred to as QDGM(1,1)). We discuss the affine properties of QDGM model. The paper employed a majorization principle to optimizing the iterative starting value of the new model, and introduced the steps of using QDGM (1, 1) to predict. Finally, there is an instance that demonstrates the new model has the best results in the four discrete grey models. It was proved that the new model greatly improves the simulation and prediction precision.
  • Keywords
    grey systems; iterative methods; quadratic programming; QDGM(I,I)); grey discrete parameters prediction model; grey system theory; iterative starting value optimization; majorization principle; quadratic time-varying discrete grey model; quadratic time-varying parameters; Accuracy; Biological system modeling; Forecasting; Predictive models; grey discrete parameters prediction; quadratic time-varing parameters; simulation and prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science (ICIS), 2014 IEEE/ACIS 13th International Conference on
  • Conference_Location
    Taiyuan
  • Type

    conf

  • DOI
    10.1109/ICIS.2014.6912166
  • Filename
    6912166